SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 3801–3810 of 4891 papers

TitleStatusHype
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds—0
Bridging Fairness Gaps: A (Conditional) Distance Covariance Perspective in Fairness Learning—0
Broad Critic Deep Actor Reinforcement Learning for Continuous Control—0
Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge—0
Burst Image Super-Resolution with Mamba—0
Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits—0
Byzantine-Resilient Distributed P2P Energy Trading via Spatial-Temporal Anomaly Detection—0
CageViT: Convolutional Activation Guided Efficient Vision Transformer—0
CAMEL: Curvature-Augmented Manifold Embedding and Learning—0
CAM-NET: An AI Model for Whole Atmosphere with Thermosphere and Ionosphere Extension—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified